表位
生物
T细胞受体
生物信息学
计算生物学
抗原
癌症
CD8型
T细胞
免疫学
免疫系统
遗传学
基因
作者
Donovan Flumens,Sofie Gielis,Esther Bartholomeus,Diana Campillo-Davó,Sanne van der Heijden,Maarten Versteven,Hans De Reu,Evelien Smits,Benson Ogunjimi,Kris Laukens,Pieter Meysman,Eva Lion
标识
DOI:10.1016/bs.mcb.2023.08.001
摘要
Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and expensive procedure that usually requires a large amount of patient cells. To maximize information from and minimize the need of precious samples in cancer research, prediction models have been developed to identify in silico epitope-specific TCRs. In this chapter, we provide a step-by-step protocol to train a prediction model using the user-friendly TCRex webtool for the nearly universal tumor-associated antigen Wilms' tumor 1 (WT1)-specific TCR repertoire. WT1 is a self-antigen overexpressed in numerous solid and hematological malignancies with a high clinical relevance. Training of computational models starts from a list of known epitope-specific TCRs which is often not available for new cancer epitopes. Therefore, we describe a workflow to assemble a training data set consisting of TCR sequences obtained from WT137–45-reactive CD8 T cell clones expanded and sorted from healthy donor peripheral blood mononuclear cells.
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